본 연구는 4차 산업혁명과 팬데믹의 환경 속에서 중소·중견기업 리더의 온라인 코칭행동이 조직성과에 미치는 영향과 그 과정에서 구성원의 직무만족과 정 서적 조직몰입의 매개 여부, 그리고 사업환경 불확실성이 이들 간의 관계를 조절하는지 검증하고자 하였다. 이를 위해 국내 다양한 업종에 속한 중소․중견기업의 구성원 중 온라인 업무 경험이 있는 350명의 자료를 수집하였고, SPSS 23.0, AMOS23.0 과 Process macro 3.5를 사용하여 실증분석을 하였다. 분석 결과는 다음과 같다. 첫째, 온라인 코칭행동은 구성원의 직무만족, 정서적 조직몰입과 조직성과에 정(+)의 영향을 미쳤다. 둘째, 온라인 코칭행동과 조직성과 간에 직무만족과 정서적 조직몰입의 매개 효과를 확인하였다. 셋째, 사업환경 불확실성은 온라인 코칭행동과 조직성과 간의 관계를 조절하는 것으로 나타났으나, 온라인 코칭행동과 직무만족 및 정서적 조직몰입과의 관계는 조절하지 않는 것으로 나타났다. 이러한 분석결과를 통해 온라인코칭행동도 대면코칭행동과 마찬가지로 조직성과에 영향을 미친다는 것을 알 수 있었으며, 따라서 현재와 같이 사업환경이 매우 불확실한 상황에서 중소·중견기업들은 온라인 코칭을 활용하고 직무만족 및 정서적 조직몰입을 증진시킴으로서 성과를 향상시킬 수 있을 것으로 생각된다.

The purpose of this study was to analyze structural relationships with regard to the effect of customer integration, which is a type of integration in the supply chain, and market orientation of supply chain on the resulting change in the supply chain and management performance. The results of analysis in this study are as follows: First, customer integration and market orientation had a positive effect on reducing the flexibility and uncertainty of SCM. The decreased flexibility and uncertainty of SCM had a positive effect on non-financial performance, which also had a positive effect on financial performance. Second, customer integration and market orientation had a positive effect on financial and non-financial performance indirectly by decreasing the flexibility and uncertainty of SCM. Third, the effect of customer integration and uncertainty of SCM on the flexibility of SCM changed depending on the position in the supply chain; the effect was larger in the distribution group. The implications based on the analysis results are as follows: It is expected that the ability to deal with market changes in the overall supply chain is improved by laying the foundation for cooperation through establishing information infrastructure, including sharing information with trade partners and integrating systems, and implementing customer integration based on these achievements. It is also necessary to consider the business types and characteristics of individual companies in establishing information infrastructure.

Sea trial tests are necessary to verify speed-power performance, and are an import contract between ship owners and shipyards. The International Organization for Standardization (ISO) published ISO 15016:2015, which specifies the correlation method between model and full-scale ships. The results of sea trials have been questioned because of the uncertainty of speed and power measurements, especially when sea conditions differ from ideal calm water conditions. In this paper, such uncertainties were investigated by utilizing the standard speed-power trial analysis procedure defined in ISO 15016:2015 through Monte Carlo simulations. It was found that the expanded uncertainty of the delivered power (PDid) at 95 % confidence interval (k = 2) was ±1.5 % under 75 % MCR conditions.

The objective of measurement of bio-signals in measurement uncertainty is not to determine the true value as closely as possible, but to determine a measured value and to assign the interval of the value. The measurement uncertainty is estimated by type A and B evaluations, depending on whether they are evaluated by statistics or the mathematical probability theory. Intraoperative neurophysiologic monitoring is used often for early detection of inherent risk relevant to neurosurgical procedures leading to permanent neurological injury, while it is still potentially reversible. In this study, we evaluated the uncertainties in somatosensory evoked potentials (SSEPs), which are used for monitoring sensory neural pathways. In a 45-year-old man who underwent cervical laminectomy, SSEPs were monitored using the ISIS IOM SYSTEM (Inomed, Emendingen, Germany) to evaluate the uncertainties. Expanded uncertainty were 0.88 mV and 1.22 ms, for amplitude and latency, respectively. Measured values and corresponding uncertainties of amplitude and latency were 2.78 ± 0.88 mV and 24.02 ± 1.22 ms, respectively. The expanded uncertainty (0.88 mV) of the amplitude was approximately 30% of the mean value (2.78 mV). A reasonable explanation for this would be the effects of variables such as electromagnetic waves (diathermy and warming blankets), temperature, blood pressure, sex and body mass index on SSEPs. Careful attention is required in interpreting SSEPs.

This paper reports an uncertainty analysis of quantitative visualization methodology for slug bubble dynamics in downward-facing nucleate boiling condition. Measurement of dynamics of slug bubble, i.e. departing speed, frequency, and diameter, is very important to predict safety margin of thermal systems in moving vehicle. By employing high speed visualization and post-processing, we quantitatively measured the volume and location of slug bubble, so that vapor generation rate and departing speed data were derived from their time differentiation. As a visualization methodology, its reliability was evaluated via uncertainty analysis. For 95% confidence interval, uncertainty of vapor generation rate and departing speed were 3% and 2%, respectively, and which were one order lower than standard deviation of those data.

The present research examines the Uncertainty-Prediction Asymmetry (UPA) hypothesis, that low certainty incidental emotions, compared to their high certainty counterparts, lead to utility overprediction and to lower forecasting error. Introduction Cognitive appraisals of emotion have been included in the state-of-the-art theory of emotion and decision-making (Lerner & Keltner, 2000; Lerner, Li, Valdesolo, & Kassam, 2015). For instance, Tiedens & Linton (2001) discuss how happiness involves appraisals of high certainty, and sadness involves appraisals of low certainty. In terms of forecasting, systematic processing is generally considered to lead to less forecasting error compared to heuristic processing. Tiedens & Linton (2001) argue that, if accuracy is the ultimate goal the individual needs to rely on more thoughtful processes. Seeking a state of certainty is more cognitively engaging and requires more cognitive resources. But how do people predict future utilities in the first place? Theoretical background Kahneman & Thaler (2006) analyze forecasting as a two-step procedure, encompassing a current prediction as well as a future event. Breaking down the present and future situation allows researchers to assess accuracy and detect how errors occur. Kahneman & Snell (1992) report that people tend to underpredict future utilities. Typically, the experienced utility is higher (i.e. more liked or less disliked) compared to the earlier prediction. In the present paper we argue that emotional uncertainty leads to utility overprediction and thus reduces forecasting error. This hypothesis is in line with the Appraisal-Tendency Framework (ATF-overview in Lerner et al., 2015). According to the ATF, an emotion may trigger a cognitive predisposition to assess future events in line with the central appraisal dimensions that triggered that emotion. Such appraisals provide a perceptual schema for interpreting subsequent situations. In the context of the present research, the certainty-uncertainty cognitive appraisal is hypothesized to trigger a predisposition that affects the utility prediction mechanism and leads to utility overprediction. This hypothesis is also in line with the uncertainty intensification hypothesis (Bar-Anan, Wilson, & Gilbert, 2009), according to which the uncertainty of experienced emotions makes unpleasant events more unpleasant and pleasant events more pleasant. The present research examines an Uncertainty-Prediction Asymmetry (UPA) hypothesis. In three experimental studies we test the hypotheses that low certainty incidental emotions, compared to their high certainty counterparts, lead to utility overprediction (H1) and to lower forecasting error (H2). Emotional certainty, as an appraisal dimension of emotions, is expected to create a prediction asymmetry through its effect on both predicted utility and forecasting error. The mediating role of heuristic processing in the relationship between emotional certainty and forecasting error is also investigated. Experiment 1 The first experiment examines the hypothesis that low emotional certainty leads to utility overprediction (H1). Eighty postgraduate students were randomly assigned to a high emotional certainty (disgust) vs. a low emotional certainty (fear) condition. Emotion induction involved exposure to pretested video clips (see Han et al., 2012). Following this manipulation, the experimental utility (a small candy bar) was distributed and participants were encouraged to consume it (see Kahneman & Snell, 1992). They were then asked to report on 13-point scales how much they liked the utility and to predict how much they would like it in the future consumption occasion (a week later). The results revealed a significant difference in predicted utility between the high (M = 2.22, SD = 1.33) and low (M =3.65, SD = 1.37) emotional certainty conditions (F = 4.43, p = 0.04, partial eta squared = 0.10). Experiment 2 The second experiment includes a “future event”, that is measures of the utility that was originally predicted, in order to also estimate forecasting error. The experiment therefore tests if (a) the main effect of emotional uncertainty on predicted utility is confirmed (H1) and (b) there is a significant main effect of emotional uncertainty on forecasting error (H2). In addition, this experiment examines whether these effects are independent of the valence appraisal dimension of emotions. Given that Experiment 1 involved two negatively valenced emotions, emotional valence (positive vs. negative) was included in the experimental design. Seventy three postgraduate students participated in a five-consecutive-days experiment. During the first day, participants were randomly assigned to a fear (negative valence, low certainty), disgust (negative valence, high certainty), hope (positive valence, low certainty) or happiness (positive valence, high certainty) condition. Specifically, participants were asked to report an experience in which they had felt this particular emotion through an Autobiographical Emotional Memory Task (AEMT) (as in Smith & Ellsworth, 1985). Following this experimental manipulation, the experimental utility (a small chocolate bar) was distributed and they were again encouraged to consume. Subsequently, they were asked to rate how much they liked and how much they would like the utility on the fifth day. Depth of processing was assessed with four items (α=0.77), adjusted from Griffin et al. (2002). Specifically, these items measured the heuristic processing performed during the prediction process. Participants were contacted again on each of the remaining four days and were asked to consume the utility and to complete a short questionnaire (comprising ratings of the consumption experience and of the predicted utility on the fifth day). The results reported here involve only the data obtained on the first and final day of the experiment, and the forecasting error was estimated as the difference between the experienced utility of the last day and the predicted utility of the first day. In line with hypothesis H1, emotional certainty had a significant main effect on predicted utility (F = 6.18, p = 0.002, partial eta squared = 0.08). Specifically, predicted utility in the low emotional certainty condition was higher (M = 2.69, SD = 1.09), compared to that of the high certainty condition (M = 0.78, SD = 1.66). There was no significant interaction effect between certainty and valence. These findings provide further support for our H1 and indicate that emotional certainty influences utility prediction irrespective of the valence of incidental emotions. Moreover, a significant main effect of certainty on forecasting error was observed (F = 4.16, p = 0.045, partial eta squared = 0.06). Forecasting error was lower in the low certainty condition (M = 0.59, SD = 1.28) compared to the high certainty condition (M = 2.19, SD = 1.48). There was no significant interaction effect. Moreover, a mediation analysis revealed that heuristic processing mediated the effect of certainty on forecasting error (p**<0.05). Experiment 3 The previous two experiments indicate that the effects of incidental emotional states on predicted utility and forecasting error may be due to the certainty-appraisal dimension of these emotional states. A possible criticism and an inherent limitation of Experiments 1 and 2 might lie on the possibility that these effects are not independent of the other appraisal dimensions. This is related to a key methodological issue. In Experiments 1 and 2, the induced emotions were different in terms of certainty or uncertainty, but these emotions might have differed in other ways and across other appraisal dimensions as well. To eliminate this possibility and to strengthen our argument, we employ here a manipulation of the certainty appraisal of the same emotion. We therefore compare predicted utility and forecasting error in the same emotional state under conditions of low and high certainty. In Experiments 1 and 2 the emotions induced are strong representatives of each side of the certainty appraisal dimension. However, emotions located in the middle of this dimension provide an interesting opportunity since they might allow us to compare their effects when they are associated with lower or higher levels of certainty. In this experiment we have chosen to focus on the emotional state of sadness. Sadness was selected because it is near the middle of the certainty-uncertainty dimension (Smith & Ellsworth, 1985). Similar manipulations of sadness have been reported in the literature (Tiedens & Linton, 2001). Sixty postgraduate students were randomly assigned to a low vs. high certainty sadness condition. High certainty participants were asked to recall and report an experience or event in which they had felt high certainty sadness (i.e. during which they understood what was happening and could predict what was going to happen next), through an Autobiographical Emotional Memory Task (AEMT) as in Experiment 2. Similarly, low certainty participants were asked to recall and report an event or experience that had generated low certainty sadness. Following the experimental manipulation, the experimental utility (a small chocolate bar) was served. Participants were again encouraged to consume some of it and were asked to complete 13-point ratings of how much they liked it and how much they would like it in the future occasion (a week later). Eight items (α=0.81), adapted from Griffin et al. (2002), measured the heuristic processing performed during the prediction process. Participants also completed ten items adjusted from PANAS questionnaire (Watson et al., 1988). A week later, participants consumed the utility and completed a short questionnaire. The results revealed a significant main effect of certainty on the predicted utility (F = 4.00, p = 0.05, partial eta squared = 0.06). Predicted utility in the low certainty sadness condition was higher (M = 4.21, SD = 1.55) compared to that of the high certainty condition (M = 3.35, SD = 1.78). A significant main effect of certainty on forecasting error was also observed (F = 5.04, p = 0.03, partial eta squared = 0.10). Forecasting error in the low certainty condition (M = -0.10, SD = 1.65) was lower compared to that of the high certainty condition (M = 1.02, SD = 1.81). A mediation analysis revealed that heuristic processing again mediated the effect of certainty on forecasting error (p**<0.05). Conclusion The contribution of this research is mostly highlighted by the counter-intuitive findings that lower certainty emotions lead to judgment with higher accuracy, as well as to an overprediction of utilities, related to their certainty counterparts. Therefore, the current findings provide support for the proposed Uncertainty-Prediction dual Asymmetry (UPA) hypothesis. Future research needs to corroborate these findings, to clarify the mechanisms underlying the observed asymmetry and to identify boundary conditions.

People face various situations that they have to decide whether to buy or not, before uncertainty is resolved. Under the uncertain conditions, it is most crucial part for consumers that they should consider the expected valuation derived from purchasing tickets or services. Thus, it is important to contemplate buyer uncertainty about future valuation. Xie and Shugan presented the relationship between spot price and advance price in a situation that involves uncertainty. Their findings provide the explicit advance pricing strategies that can create profit improvements (Xie & Shugan, 2001). Their findings lay a foundation of this problem, because buyers are almost always not sure about their future valuations for most services (Xie & Shugan, 2001). In addition to these findings, the researchers found that profits under option pricing strategy outperform those from advance pricing strategy (Preethika Sainam, 2010). They introduce the concept of consumer options and analytically prove that consumer options can make more profits and also can protect consumers from the pitfall derived from unwanted outcomes (Preethika Sainam, 2010). In this paper, we want to consider this problem under more complex and real circumstances. We include one more pricing strategy, discounted advance pricing, which is often called early bird pricing. Furthermore, we divide consumers in two types, risk-neutral consumers and risk-averse consumers. We present a simple analytical model in what conditions each pricing strategies can out-perform others based on consumer types and capacity types.

A small dam is of hydraulic structures, which is always exposed to risk by flood, and it’s very important to ensure structural safety. A probabilistic analysis, quantifying variable as a risk factor to ensure safety of small dam, identifying its coefficient of variation, which has become increasingly important. In this study, the risk of seepage failure of foundation within a small dam was estimated based on flood scenarios by rainfall quantile. The final compound risk was evaluated combining probabilities, related to seepage failure and flood level. The seepage failure probability was estimated by performing seepage analysis depending on the water level difference between upstream and downstream in small dam. The probable flood level was estimated by considering hydraulic uncertainty associated with channel geometry, and movable gate operation during the flooding season, applied a probable flood considering hydrologic uncertainty evaluated by Bayesian approach. The safety evaluation of small dam with probabilistic-based compound risk expect to use the index for hydraulic structure design in the future.

In this study, the effects of anticipated regret and perceived uncertainty on price sensitivity or purchase hesitation in overseas purchasing are analyzed along with the effects of price sensitivity on purchase hesitation. The survey was conducted among internet fashion consumers with experience in overseas purchasing and 480 responses were used in the data analysis. The results showed the psychosocial anticipated regret positively influenced the price importance, and the service, product and psychosocial anticipated regret positively influenced the price search. The preference and psychology uncertainty positively influenced the price importance, and the information and psychology uncertainty positively influenced the price search. The price importance positively influenced payment stage hesitation and shopping cart abandonment, and the price search positively influenced purchase hesitation in overseas purchasing. The functional, service and psychosocial anticipated regret positively influenced payment stage hesitation, and the service and psychosocial anticipated regret positively influenced shopping cart abandonment and overall purchase hesitation. In addition, the perceived uncertainty positively influenced the payment stage hesitation, and the information and psychology uncertainty positively influenced the shopping cart abandonment and overall purchase hesitation. The results of this study will be helpful for developing the marketing strategy for customer relationship management for overseas internet shopping web-sites.